Computer databases store ever-increasing amounts of data for use by different applications. For example, a data center for a web-based application such as email may employ a number of data storage devices that are geographically distributed. Each location may include a cluster or group of number of storage servers with databases for storing data relating to users' email accounts, such as the text of emails, preferences for displaying emails and so forth. In such large, geographically distributed data centers, or even at a single location, it is important for IT personnel, business managers and others to be able to assess the availability of the databases, such as for setting internal performance goals or service level agreements (SLAs) with outside parties. However, databases may experience downtime due to software upgrades such as patch installations, software hardware failures, maintenance, decommissioning of old hardware, resource balancing, and the like. Currently, the assessment of downtime is a manual, time-consuming task, and the techniques used are often inconsistent and erroneous. As a result, there can be debates over perceived vs. real performance, and resources may be allocated non-optimally.
A solution is needed for assessing the availability of databases or other computer resources in an automated manner which is compatible across different data storage systems, and which provides an accurate basis for setting service level agreements.